Workshop in Biostatistics

DATE: April 21, 2016
TIME: 1:30 - 3:00 pm
LOCATION: Medical School Office Building, Rm x303
TITLE: Statistical Methods for Single-Cell Gene Expression Data

Emma Pierson
Computer Science, Stanford


The growing use of single-cell gene expression data offers insight both into normal cellular function and into diseases such as cancer, but single-cell data presents new challenges which standard clustering and dimensionality reduction methods are not designed to confront. We show that performance of standard algorithms suffers on single-cell data and present several new models which yield better performance on both simulated and biological data.

Suggested reading:

Emma Pierson and Christopher Yau.  ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis Genome Biology 2015, 16:241.